• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.803-814
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• 2016

Recent times have seen an exponential increase in the amount of spatial data, which is in many cases associated with temporal data. Recent advances in computer technology and computation of hierarchical Bayesian models have enabled to analyze complex spatio-temporal data. Our work aims at modeling data of daily average nitrogen dioxide (NO2) levels obtained from 25 air monitoring sites in Seoul between 2003 and 2010. We considered an independent Gaussian process model and an auto-regressive model and carried out estimation within a hierarchical Bayesian framework with Markov chain Monte Carlo techniques. A Gaussian predictive process approximation has shown the better prediction performance rather than a Hierarchical auto-regressive model for the illustrative NO2 concentration levels at any unmonitored location.

• Journal of the Korean Data and Information Science Society
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• 제27권5호
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.778-784
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• 2005

Miniaturization of computing devices, and advances in wireless communication and positioning systems will create a wide and increasing range of database applications such as location-based services, tracking and transportation systems that has to deal with Moving Objects. Various types of queries could be posted to moving objects, including past, present and future queries. The key problem is how to model the location of moving objects and enable Database Management System (DBMS) to predict the future location of a moving object. It is obvious that there is a need for an innovative, generic, conceptually clean and application-independent approach for spatio-temporal handling data. This paper presents behavioral aspect of the spatio-temporal databases for managing and querying moving objects. Our objective is to impelement and extend the Spatial TAU (STAU) system developed by Dr.Pelekis that provides spatio-temporal functionality to an Object-Relational Database Management System to support modeling and querying moving objecs. The results of the impelementation are demonstrated in this paper.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• 한국IT서비스학회지
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• 제9권1호
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• pp.127-139
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• 2010

Due to the development of information technology and business related to geographical location of customer, the need for the storage and analysis of geographical location data is increasing rapidly. Geographical location data have a spatio-temporal nature which is different from typical business data. Therefore, different methods of data storage and analysis are required. This paper proposes a multi-dimensional data model and data visualization to analyze geographical location data efficiently and effectively. Purchase order data of an online farm products brokerage business was used to build prototype datamart. RFM scores are calculated to classify customers and geocoding technology is applied to display information on maps, thereby to enhance data visualization.

• 한국대기환경학회지
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• 제24권3호
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• pp.284-299
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• 2008

Emission input modules was developed to produce emission input data and change some profiles for Sparse Matrix Operator Kernel Emissions (SMOKE) using Clean Air Policy Support System (CAPSS)'s activities and previous studies. Specially, this study was focused to improve chemical speciation and temporal allocation profiles of SMOKE. At first, SCC cord mapping was done. 579 SCC cords of CAPSS were matched with EPA's one. Temporal allocation profiles were changed using CAPSS monthly activities. And Chemical speciation profiles were substituted using Kang et al. (2000) and Lee et al. (2005) studies and Kim et al. (2005) study. Simulation in Seoul Metropolitan Area (Seoul, Incheon, Gyeonggi) using MM5, SMOKE and CMAQ modeling system was done for effect analysis of changed input modules of SMOKE. Emission model results adjusted with new input modules were slightly changed as compared to using EPA's default modules. SMOKE outputs shows that aldehyde emissions were decreased 4.78% after changing chemical profiles, increased 0.85% after implementing new temporal profiles. Toluene emissions were decreased 18.56% by changing chemical speciation profiles, increased 0.67% by replacing temporal profiles as well. Simulated results of air quality were also slightly elevated by using new input modules. Continuous accumulation of domestic data and studies to develop input system for air quality modeling would produce more improved results of air quality prediction.

• 전자공학회논문지CI
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• 제45권3호
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• pp.40-46
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• 2008

원격탐사 영상과 고도자료를 사용하여 지구환경을 3차원으로 시각화할 수 있는데, 이것은 지구과학분야에서 정보를 3차원 공간에서 탐색하고 분석하는 새로운 패러다임을 제공해준다. 지구환경을 보다 현실감 있게 시각화하고 이를 통해 공간적 특징이나 객체 지형들 간의 관계를 분석할 수 있도록 하려면 3D 공간 표현의 지원이 필요하다. 이를 위해서는 다양한 2D, 3D 공간자료와 관련 벡터 자료가 통합되어야 하고, 또한 지질이나 지표 객체들 간의 상대적 위치와 위상학적 관계가 통합되어 함께 다루어져야 한다. 이러한 이유로 지구과학 및 지구환경 문제의 3차원 시각화에서는 3차원 모델링과 위상 분석, 데이터베이스가 함께 고려되어야 한다. 본 논문에서는 지구과학 및 지구환경 분야에서 3차원적 특성을 포함한 동적모형 개발과 시뮬레이션 환경 기반을 제공하도록 원격탐사 자료를 이용하여 시각화하는 방법과 자료추출 및 관리, 3차원 가상공간에서 동적 모형화를 활용하는 방법론에 관하여 연구되었다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1272-1281
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• 2006

RFID 기술을 이용함으로써 얻을 수 있는 많은 장점으로 인하여, 공급망에서 발생하는 실시간 제품 정보를 수집하고 관리하기 위하여 RFID 기술이 도입되고 있다. 기존의 RFID 기반의 공급망 관리 시스템은 제품의 위치에 따른 가시성은 확보할 수 있지만, 제품의 모든 상태에 따른 가시성은 확보하지 못한다는 단점이 있다. 이러한 단점을 해결하기 위해, 본 논문에서는 공급망 상의 제품 이동을 계획하고, 제품이 계획에 따라 이동할 때 발생하는 정보를 실시간으로 모니터링하고 통제할 수 있는 제품 상태 기반의 물류 통제 시스템을 설계하고 개발하였다. 이를 위해 본 연구에서는 첫째, 공급망에서 발생하는 제품 상태의 정의와 상태 변화의 흐름을 state chart로 표현하고, 둘째, 공급망에서의 폐쇄형관리 패러다임을 통한 제품 통제(감시 및 예외처리)를 정의하였으며, 셋째, Temporal data modeling을 통해 RFID 데이터 기반의 Database를 설계하고, 마지막으로, Publish/Subscribe 모델을 통해 효율적인 제품 상태 기반의 물류 통제 시스템 아키텍처를 설계하였다.

• 한국수자원학회논문집
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• 제55권4호
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• pp.257-266
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• 2022

국지성 호우 및 설계빈도 이상 강우의 증가로 침수피해가 매년 증가하고 있으며 이에 따라 홍수 조절 및 방어를 위한 수공구조물의 중요성이 증가하고 있다. 수공구조물은 목적과 성능에 따른 설계가 이루어지고 있고 홍수량이 중요한 산정 요소이나 국내에서는 관측자료의 신뢰성 부족 및 데이터의 부족으로 인하여 수공구조물 설계를 위한 수문해석 입력자료로 사용되는 설계강우량은 정확한 확률강우량의 산정과 시간분포가 중요한 요소로 작용한다. 실무에서는 Huff의 4분위 방법의 누가우량백분율을 이용하여 설계강우량의 시간분포 회귀식을 산정하고 있으며 분위별 곡선에 대한 회귀식은 전반적으로 정확도가 높게 나타나는 6차 다항회귀식을 일률적으로 사용하고 있다. 본 연구에서는 실무에서 일반적으로 설계강우량의 시간분포를 위해 사용하고 있는 Huff의 4분위 방법의 누가우량백분율을 이용하여 통계 모델링에서 간결함의 원리에 따라 변수선택법을 이용하여 시간분포 회귀식을 유도하였으며, 유의성 검정을 통한 시간분포 회귀식의 검증을 실시하였다. 변수선택법과 유의성 검정을 통한 시간분포 회귀식 산정 결과 전진선택법과 후방제거법의 장점을 모두 가지고 있는 단계선택법을 이용하여 시간분포 회귀식을 유도하는 것이 가장 적합한 것으로 분석되었다.

• 한국물환경학회지
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• 제28권6호
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• pp.866-881
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• 2012

Han River is a complex water system consisting of many lakes. The water quality of Lake Paldang is significantly affected by incoming flows, which are the South and North branches of the Han River, and the Kyungan Stream. In order to manage the water quality of the Lake Paldang, we should consider the entire water body where the incoming flows are included. The objectives of this study are to develop an integrated river and lake modeling system for Han River system using a multidimensional dynamic model and evaluate the model's performance against field measurement data. The integrated model was calibrated and verified using field measurement data obtained in 2007 and 2008. The model showed satisfactory performance in predicting temporal variations of water level, flow rate and temperature. The Root Mean Square Error (RMSE) for water temperature simulation were $0.88{\sim}2.13^{\circ}C$ (calibration period) and $1.05{\sim}2.00^{\circ}C$ (verification period) respectively. And Nash-Sutcliffe Efficiency (NSE) for water temperature simulation were 1089~0.98 (calibration period) and 0.90~0.98 (verification period). Utilizing the validated model, we analyzed the spatial and temporal distributions of temperature within Han River system. The variations of temperature along the river reaches and vertical thermal profiles for each lakes were effectively simulated with developed model. The suggested modeling system can be effectively used for integrated water quality management of water system consisting of many rivers and lakes.